Virtual healthcare communication platform

ABSTRACT

A system comprising a pair of devices to enable communication between a first person and a second person; a body-suit to be worn by the first person; and a model replica of the body-suit configured to receive the tactile stimuli and/or the electrical stimuli from the second person and to convert the tactile stimuli and/or the electrical stimuli into the electrical signals which are conveyed to the body-suit over a network; wherein the body-suit is configured to replicate the tactile stimuli and/or the electrical stimuli of the model replica and convey the tactile stimuli and/or the electrical stimuli to the first person; and wherein the system allows a human to send a physical sensation of touch remotely to another human.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 16/437,182, filed Jun. 11, 2019 (now allowed asU.S. Pat. No. 10,950,332, to be issued on Mar. 16, 2021), which is acontinuation application of U.S. Ser. No. 15/824,662, filed Nov. 28,2017 (Now U.S. Pat. No. 10,319,472, Issued on Jun. 11, 2019), which is acontinuation application of U.S. patent application Ser. No. 13/798,745,filed Mar. 13, 2013 (Now U.S. Pat. No. 9,830,423, Issued on Nov. 28,2017), which is a continuation-in-part of U.S. patent application Ser.No. 13/668,337, filed Nov. 5, 2012, entitled “Online Social Interaction,Education, and Health Care by Analysing Affect and Cognitive Features,”(Now U.S. Pat. No. 9,819,711, Issued on Nov. 14, 2017), which claimspriority to the U.S. provisional application No. 61/720,405, entitled“The Next Generation of Virtual Live Education” filed Oct. 31, 2012 andU.S. provisional application No. 61/719,980, entitled “Online SocialInteraction, Education, and Health Care by Analysing Affect andCognitive Features” filed Oct. 30, 2012, which are incorporated hereinin their entirety by reference.

In addition, U.S. patent application Ser. No. 13/455,133, entitled“VIRTUAL COMMUNICATION PLATFORM” filed Apr. 25, 2012, which claimsbenefit from U.S. Provisional application No. 61/625,949, entitled “SWAPThe Next Generation of Virtual Communication Platform,” filed on Apr.18, 2012, and U.S. Provisional application Ser. No. 61/556,205, entitled“SWAP: FUTURE OF VIDEO CHATTING,” filed Nov. 5, 2011.All the above applications are incorporated herein in their entirety byreference. All U.S. patents and publications listed in this applicationare incorporated herein in their entirety by reference. This applicationis also related to the U.S. patents and publications listed inAppendix 1. These U.S. patents and publications listed in Appendix 1 areincorporated herein in their entirety by reference.

BACKGROUND

According to International Data Corporation (IDC), a global provider ofmarket intelligence, video communications is one of the most promisingindustries with the potential to create a market of at least 150 millionpeople in America alone in the next five years.

Certain video communication platforms for groups of individuals tocreate and share information, interact with each other through thesoftware and generally use the software to achieve an individual orgroup objective are currently available. Generally, these systems storethe collaboration for future reference and further discussion orcollaboration. However, these systems have several limitations that havebeen addressed herein. Also, novel solutions for these limitations areprovided herein.

SUMMARY

The embodiments herein relate to a method of establishing acollaborative platform comprising performing a collaborative interactivesession for a plurality of members, and analysing affect and cognitivefeatures of some or all of the plurality of members.

In one embodiment, some or all of the plurality of members fromdifferent human interaction platforms interact via the collaborativeplatform,

One embodiment can further comprise displaying of targetedadvertisements or notifications based on the context of the interactivecollaborative session.

One embodiment can further comprise measuring effectiveness of thedisplaying of targeted advertisements or notifications.

One embodiment can further comprise integrating an application or adevice within the collaborative interactive session.

Another embodiment relates to a computer implemented system comprising:a storage medium configured to store a collaborative interactive sessiondata; and a processor configured to perform a collaborative interactivesession for a plurality of members, wherein the system analyses affectand cognitive features of some or all of the plurality of members.

In one embodiment, some or all of the plurality of members fromdifferent human interaction platforms interact via the collaborativeinteractive session, wherein the different human interactions platformscomprise social media platforms.

In one embodiment, the system is further configured to display targetedadvertisements or notifications based on the context of the interactivecollaborative sessions.

In one embodiment, the system is further configured to measureeffectiveness of the displaying of targeted advertisements ornotifications.

In one embodiment, the system is further configured to integrate anapplication or a device within the collaborative interactive session.

In one embodiment, the system comprises a sound and/or video hub,wherein the sound and/or video hub allows any member of the plurality ofthe members to play a song and/or a video and simultaneously allows someor all of the plurality of members to listen and/or watch the songand/or the video played.

In one embodiment, the system comprises audio and/or video synopsis ofthe collaborative interactive session for the plurality of members usinga sound and image-processing technology that creates a summary of anoriginal full-length audio and/or video.

Another embodiment relates to a tangible non-transitory computerreadable medium comprising computer executable instructions executableby one or more processors for establishing a collaborative platformcomprising performing a collaborative interactive session for aplurality of members, and analyzing affect and cognitive features ofsome or all of the plurality of members.

In one embodiment, some or all of the plurality of members interact fromdifferent human interaction platforms.

One embodiment could further comprise computer executable instructionsexecutable by one or more processors for displaying of targetedadvertisements or notifications based on the context of the interactivecollaborative sessions.

Embodiments herein relate to a system comprising: a first communicationdevice configured to present data to and/or receive data from a healthcare practitioner; a second communication device configured to presentdata to and/or receive data from a patient, which could be a human oranimal; a processor configured to determine values of one or moremetrics that characterize the patient's mental state based data receivedfrom the patient via the second communication device; a storageconfigured to store the metrics.

In one embodiment, the storage is configured to store long term healthdata of the patient.

In one embodiment, the storage is configured to store short term healthdata of the patient.

In one embodiment, the data received from the patient comprise a video.

In one embodiment, the data received from the patient comprise a sound.

In one embodiment, the data received from the patient comprise a drawingor handwriting.

In one embodiment, the data received from the patient comprisecommunication from the patient to another patient.

In one embodiment, the data received from the patient comprise physicalcharacteristics measured from the patient in real-time.

In one embodiment, the data received from the patient comprise thepatient's facial expression.

In one embodiment, the data received from the patient comprise thepatient's pupillary dilation.

In one embodiment, the data received from the patient comprise thepatient's performance in a game.

In one embodiment, the storage comprises a knowledge base.

Another embodiment relates to a method of diagnosing a patient, whichcould be a human or animal, the method comprising: collecting dataconveying information about symptoms experienced by the patient; storingthe data conveying information about symptoms in a database on a virtualcommunication platform; generating keywords conveying symptomsexperienced by the patient; and performing a federated search to obtaina diagnosis of the patient's disease condition, wherein a federatedsearch comprises searching through a database compiled on the virtualcommunication platform correlating symptoms to disease conditionsobtained from a virtual communication platform.

In one embodiment, the keywords are generated using data collected fromthe virtual communication platform.

One embodiment further comprised monitoring vital signs of the patientover a pre-determined period of time following the diagnosis and loggingthe data on the virtual communication platform.

In one embodiment, the vital signs comprise one or more of height,weight, heartrate, variation in heart-rate, blood glucose level, andblood pressure.

In one embodiment, the vital signs are monitored using sensors embeddedin a body-suit or jacket worn by the patient.

In one embodiment, the body-suit or jacket is configured to providemechanical and/or electrical stimuli to a part of the patient's bodycovered by the body-suit or jacket.

In one embodiment, the body-suit or jacket is further configured to becontrolled remotely using a using a computer.

In one embodiment, the body-suit or jacket worn by the patient isconnected to a model replica of the body-suit available at a remotelocation.

In one embodiment, the model replica of the body-suit is configured toreceive tactile stimuli and convey the tactile stimuli through aconnection to the body-suit or jacket worn by the patient.

In one embodiment, the body-suit is configured to replicate the tactilestimuli received through the connection from the model replica andconvey the tactile stimuli to the patient wearing the body-suit.

Another embodiment relates to a system for providing tactile and/orelectrical stimuli remotely, the system comprising: a body-suit to beworn by a human or animal, the body-suit comprising one or moreactuators configured to convert electrical signals to tactile and/orstimuli, wherein the body-suit is configured to convey the tactileand/or electrical stimuli to a body part of the human or animal; a modelreplica of the body-suit configured to receive tactile stimuli from ahuman or animal and convert the tactile stimuli into electrical signalscapable of being parsed by a computer, wherein the model replica isavailable at a location remote from the patient, wherein the modelreplica and the body-suit are connected over a network configured toconvey the electrical signals from the model-replica to the body-suit.

In one embodiment, the body-suit is configured to cover one or more ofarms, torso, neck, throat, legs, hands and feet of the human.

In one embodiment, the body-suit and the model replica each areconnected to one or more computers.

In one embodiment, the one or more computers connected to each of thebody-suit and the model replica are connected through the Internet.

In one embodiment, the body-suit is configured to replicate tactilestimuli received by the model replica and convey the tactile stimuli tothe human.

In one embodiment, the model-replica is a virtual model of human.

In one embodiment, the body-suit is configured to provide electricalstimuli to the human based on signals received from the virtual model.

In one embodiment, the body-suit comprises sensors configured togenerate output signals in response to movement by the human.

In one embodiment, the body-suit is further configured to convey theoutput signals to the model replica.

In one embodiment, the model replica is configured to convert the outputsignals received from the body-suit into tactile stimuli.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featurescan become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 shows an embodiment of data passing through the SWAP platform,wherein data is acquired and the multimedia segmented and analysed.

FIG. 2 shows an embodiment of chatting threads.

FIG. 3 shows an embodiment of profile appearance.

FIG. 4 shows an embodiment of the analysis of data through SWAP for‘close friends’.

FIG. 5 shows an embodiment of e-learning showing an user interface forstudying from a video lecture.

FIG. 6 shows an embodiment of a virtual classroom with e-material usedas learning medium, based on study of eye movement, pupillary dilationand facial study.

FIG. 7 shows an embodiment of a user interface.

FIG. 8 shows an embodiment of a collated version of the user interface.

FIG. 9 shows an embodiment of how insurance or health care companieswill acquire date through the cell phone of a client.

FIG. 10 shows an embodiment of how the media acquired by SWAP is goingto be analyzed.

FIG. 11 shows an embodiment of a non-invasive patient tracking method.

FIG. 12 shows a flow diagram that delineates possible trackingmechanisms.

FIG. 13 shows a flow diagram of an overview of SWAP's functionalities inhealthcare delivery.

FIG. 14 shows a flow diagram showing SWAP's ability to provide a dynamiccollaborative platform.

FIG. 15 exemplifies the added benefits of virtual healthcare deliverythrough SWAP.

FIG. 16 shows a flow diagram showing the ability of SWAP healthcaredelivery to form collaborations in treating a patient.

FIG. 17 shows a flow diagram showing SWAP's ability to collect criticaldata from patient interaction and consolidate into a patient's profilefor subsequent analyses

FIG. 18 shows a flow diagram for transmission of two way touchsensation.

FIG. 19 shows a flow diagram for transmission of one way touchsensation.

DETAILED DESCRIPTION

Large amount of online media that is transferred is merged providingconvenience to user. This data is analysed to find out affect andcognitive state. Utilising this data, a new form of social interactionplatform is developed which will incorporate many features of real humaninteraction.

The term “affect” refers to the experience of feeling or emotion. Affectis a part of the process of an organism's interaction with stimuli. Theword also includes affecting display, which is a facial, vocal, orgestural behavior that serves as an indicator of affect.

The term “cognitive state” refers to the state of exploring internalmental processes, for example, to study how people perceive, remember,think, speak, and solve problems.

SWAP is the acronym of an embodiment of a virtual communication platformsystem described herein. SWAP and a virtual communication platformsystem are used synonymously in this application.

Embodiments herein relate to SWAP, which can be a web-based applicationthat serves as a multi-dimensional platform for peer-to-peercommunication. Current video communication services such as Skype onlyprovide basic face-to-face contact pathways—the interaction is limitedto text, audio, and video. SWAP integrates collaboration withcommunication. It streamlines the base services of peer-to-peer text,audio and video communication with interaction on various collaborativeplatforms as well as with individual web-based activity. SWAP canincorporate existing streams of social media.

SWAP strives to be the global leader in providing a unifiedcollaboration platform using Internet communication media whileenhancing the capabilities of virtual interaction of people from allwalks of life. SWAP can provide young adults with a video communicationsapplication that integrates multiple streams of online media withvirtual interaction. SWAP can provide a unified platform that allowsusers of any social media service, such as Facebook or Google+, tointeract on, removing the fragmentation within social mediacommunication. This platform also combines text, audio, and videocommunication with collaboration in the areas of academia, music, andrecreational activities such as gaming, extending the capabilities ofcurrent virtual communication.

This application can be organized into several spheres of interactionknown as “globes”. Each globe can provide a base interaction formultiple users to collaborate. Our application can integrate thesecollaboration platforms with a video feed to enhance overall virtualinteraction.

The data passing through the SWAP platform will be acquired and themultimedia will be segmented and analysed. This can be seen in FIG. 1.FIG. 1 depicts the SWAP platform that solves the problem offragmentation and provides a seamless connection between users fromseparate platforms. These two separate platforms are integrated by SWAP.Interactions between User 1 and User 2 are then sent for analysis. Theseinteractions are used in the Swap+ Profile, Elearning, and SWAP Project.

The derived information from analysis such user emotion and mentalstates will be utilised in functioning of 3 major SWAP features—

1. Profiles (SWAP+) 2. Targeted Advertisement

3. Smart ELearning (addition to the chalkboard and virtual classroomglobe)

SWAP+ Profiles

The way most social networking sites function, they mainly act as agreat platform for data storage, sharing and communication. But theythese are all a far cry from true social interaction simulation in otherwords in no way are these anywhere near how we interact in society. Thusthe profiles of SWAP+ will be a system which will be much closer to howwe remember people, conversations and moreover how we forget. The largeamount of data that get passed through the SWAP platform will beanalyzed and this data will be used to shape the SWAP+ profiles. The wayother people's SWAP+ profiles will appear to us. In this area we try tomimic the way in which we remember people. The profile's emotion feelwill be the general emotion that we generally exhibit when wecommunicate that with that person through any form of media (video, textor speech) (obtained from analyzed data from conversations takingplace). Keeping in trend with how we remember people in reality, sincehow a person is seen by is strongly shaped with event and experiences weshare with that person. The profile of the person will bear events,having strong emotions behind them. Any sort media—like text, speech,video or pictures. Texts can be presented simply as they are, videoswill we presented like snapshots with the option to be played by theuser.

The SWAP+ profile can include:1. Chatting threads (as depicted by FIG. 2)2. Profile appearance (as depicted by FIG. 3)3. Close friends (as depicted by FIG. 4)

1. Chatting Threads

The basic flaw which makes social interactions unrealistic is that everybit of data is remembered, unlike the case in real-life dailyinteractions. To replicate these communications that will be happeningthrough SWAP+ will follow a similar pattern. The comments of the threadwill slow start to deteriorate i.e. fade away. The period after whichthe part of the thread is completely forgotten will be a sort ofthreshold time, which will be close to average human being time formemory retaining. Memories having high cognitive strain or emotionattached will have much higher threshold time.

In FIG. 2, the comments of the thread will slow start to deterioratei.e. fade away. The period after which the part of the thread iscompletely forgotten will be a sort of threshold time, which will beclose to average human being time for memory retaining. Memories havinghigh cognitive strain or emotion attached will have much higherthreshold time. This example shows a conversation between two friendsdiscussing “last night's party.” The initial conversation contains lowemotionally attached or insignificant conversation (e.g. “Hey!” “Whathappened?” “Yeah?”). In the decayed conversation, however such aspectsof the conversation are decayed into visually smaller bubbles. Thelarger bubbles include phrases associated with high cognitive strain oremotion attached. In this example, one friend tells the other “I toldmom about how I lost her gold necklace.” This phrase is the largestbubbles, assuming that the friend was experiencing significantemotion—including perhaps anxiety, fear, etc.

2. Profile Appearance

In FIG. 3, the profile of SWAP+ will be dynamic in nature constantlychanging reflecting the mental state of the user. The real-time mentalstate will be determined from the various analysis methods, which willbe applied on the data passing through SWAP. Under a state of extremeemotion such as depression the user profile will be able to reflect thisstate. This will allow for other people to be notified of the user'semotional state and hence help him get back normalcy throughcommunication. Through analysis ‘close friends’ can also be identifiedwho under the above-mentioned situation will be notified. In thisexample, we see Abhishek Biswas' profile as seen by his girlfriend.Note: this profile is individualized. His girlfriend can see all theimportant conversations between them (as “decayed conversation”feature.) These conversations include highly emotional both positive andnegative phrases. Also, highly emotional paused scenes from videos willappear as well as pictures that have been discussed in emotionalconversations.

3. Close Friends

FIG. 4 demonstrates the analysis of data through SWAP for ‘closefriends’. The analysis will allow the application to identify peoplewith whom the user has discussions of high emotional content. A databaseof sorts can be created which will store people with whom the user hasdiscussion of high emotional content such as high positive emotioncontent, high negative emotion content, people with whom throughcommunication emotion changes from negative to positive. Also, peoplewith whom there isn't communication of high emotion content but volumeand frequency of communication is very high, these people will also beidentified as ‘close friends’. Whenever the user is in a state ofemotional extreme then the user's profile will be highlighted in thehomepages of the ‘close friends’. In this example, the friend whoseprofile shows high levels of distress is the largest. The user canvisually identify this friend and try to help her. The second largestpicture is also a friend who is visually distressed (which is seenthrough emotions detected on his profile) and is therefore seen as alarge image. The third largest image is the user's girlfriend's profile.Although her profile does not show high emotional context, her profileimage is highlighted because of the high volume and frequency ofcommunication.

E-Learning

In virtual classroom or chalkboard feature the user may be required togo through leaning material or modules and solve problems. Based onobservation of Pupil dilation the cognitive load on user's mind can befound out. If the user is under high cognitive stress for prolongedperiod it is indicative that the user is unable to make progress withcurrent material or problem. Hence more comprehensive material may beprovided and in case problems a hint or a different problem may beprovided. Similarly, the pupil study may also indicate the course andproblems may not cause appreciable cognitive strain so in this case acourse which is less comprehensive and problems of higher difficulty maybe presented. The SWAP feature will allow people from different videocommunication platforms to join into a virtual classroom. This virtualclassroom will allow for multiple people to join at same time the coursebeing taught will customized for each individual user. Thus, studentgets all the benefits of study in a classroom such discussion, debating,interactive doubt clearance, observing point of view of peers. At thesame time the course is modified as peer the learning capacity andmental level of each individual student.

So as the all students join the virtual classroom, they all start outwith the same course material and as they carry forward with class,constantly each student cognitive load level, attention, stress is beingmonitored. And based on this data material is modified that will enablemaximum learning will be provided. Apart from pupillary dilation andvideo analysis of face, eye tracking will allow monitoring the movementof the eyes hence it will be possible to see whether that user is beingable to focus on the material. Using eye tracking technology we can findthe place where the user is looking at and pattern recognition can beutilized to find whether the material being presented is being read ornot for example regularized movement of eyes indicate that the user isfollowing the material presented and whereas wandering and randommovement of eyes are indicative that the material is not being followed.

The virtual classroom element of SWAP will have advanced tools tosimulate real classroom like environment. The nature learning may be of2 types; video lecture and course material.

FIG. 5 shows the user interface for studying from video lecture. Thefollowing features are present: a notepad where the user can take roughnotes, inventory of study aids (like calculator), formula manual (forthe course being studied), and access to all rough notes. The work areacontains questions and problems that will be asked to the user as eachsub segment of the video lecture is completed for those of who finishthe problems quickly more problems will be asked and the next subsegment may start only after the minimum number of questions has beencompleted by everyone. The user will be able to communicate with hisother peers and ask them for help or doubt clearance (similar to realclassrooms). The feature will also be provided that allows for personwho is communicating with user to share his work sheet and help insolving and understanding the problem. As can be seen in this example,the lecture is synchronized with the notes in the formula manual beingdisplayed. Also, based on eye movement, pupillary dilation and facialstudy of other peers, the student (or teacher) can detect the amount ofdifficulty or ease his/her peers is having with the class and theproblems.

FIG. 6 shows a virtual classroom with e material used as learningmedium, based on study of eye movement, pupillary dilation and facialstudy. The material will be constantly modified and since all peers willbe present constant discussion will also be taking place.

If it is observed that the user wasn't taking in the course then pop upquestions will be presented on the work area, to check the usersunderstanding hence allow for optimised learning.

Also, based on eye movement, pupillary dilation and facial study ofother peers, the student can detect the amount of difficulty or easehis/her peers is having with the class and the problems. Areas that seemto be confusing for the student will be noted down and at the end ofeach study session these areas will be reviewed.

SWAP Projects

FIG. 7 shows an embodiment of a user interface. For example, anotherfeature that will be present along with the education globe is a singlesheet that can be shared across an entire group. All members of thegroup can make modifications to the sheet simultaneously. All editingand word processing features will be made available. This will allow forrapid completion of project with different parts (e.g. one person may bedrawing up some part while others may be writing) being done bydifferent people. In FIG. 7, for example, Linda, Jenny, and Robert canall see each other's' videos. The “Toolbar” includes all possiblesoftware devices (e.g., tables, different languages, presentation tools,graphical tools, etc.) In this image, one of the users is able to seewhat he/she has entered into the project.

Since all progress being made is constantly visible to all the usersworking on it, a seamless integration will be possible. In factdifferent people can comment and suggest changes to some or more partsbeing done by someone else. Constant discussion and visibility amongstthe different team members will also be facilitated through audio andvideoconference, which will run in parallel with the SWAP Projectfeature. This will have huge utility in corporate sector, whichgenerally have members working on single project scattered all over theglobe.

FIG. 8 shows an embodiment of a collated version of the user interface.On a single screen, smaller images of various different types ofsoftware applications can be presented. Also each user's specific partis labelled automatically with their name. Thus, users are able to seethe different segments of the project that are being completed by otherusers.

Targeted Advertisements

Advertisement will be presented to users based ona. Keyword matchingb. Based on knowledge of user's real-time emotional state.c. Geographic location and movement pattern (for people using mobileaccess medium like cell phones or tablets)

The advertisements that will be presented will be guided based on thecontent of the conversation, the mood of the user and the feature thatof SWAP that is being used.

For example people who show high level of cognitive stress may besuggested stress-relaxing medicine, names of specialists and people.People showing emotional extremes like extreme depression may besuggested holiday destinations and retreats, or books.

For mobile users the geographical location, path and movement pattern ofthe user will be taken into account to provide location based targetedadvertisement where product that might appeal to user (predicted bytaking into factors like nature of conversation, or media beingobserved, mood of the user and geographical position). This will enableadvertisement agencies to provide extremely specific advertisement.

Healthcare (Remote Diagnosis)

Advanced application can be developed which will collect data generatedfrom cell phones and transfer these to service provider who will analysethe data and transfer it to the healthcare agencies who can then providediagnosis on basis of the data provided.

Advancement in cloud computing enables us to utilise same apps fromdifferent computing devices like tablets, computers, laptops and cellphones. The apps thus developed will not device or platform specific butwill only be user specific, they will have an inventory of data miningmechanisms and depending on the device being used select mechanisms willbe used.

Combination of data collected from the multiple sources will used todetermine lifestyle of the person and this can be used by healthcare andinsurance industries. This cycle is depicted in FIG. 9, which shows anembodiment of how insurance or health care companies will acquire datethrough the cell phone of a client. The cellular data will go through atelecom operator, through a 3^(rd) party service provider, who willcollect and analyze the data and return it back to the company.

3rd party provider can collect this data only after approval from theindividual who owns the cellular device over a set period of time. Thedata can be used by the individual for personal usage or along withhis/her doctor for health analysis. For example, an individual who isfighting with obesity can have his/her cellular data tracked for onemonth. After analysis of this data, the doctor and patient (e.g., anobese individual) can work together to target some of the problems thatthe patient. On the other hand, health insurance companies can use thisdata after approval from the potential customer to determine howhealthily he/she is living. If the behavioural choices, emotions, andother everyday actions of the customer seem to promote healthylifestyle, the insurance company can give discounted rates to such acostumer. There are three methods by which current day smart phones candetermine the lifestyle, behaviour, or emotions of a person. Time andlocation, the audio vector of the cellular device, and typingcharacteristics can be used to analyse a person's health. This data willbe collected over a span of time.

Lifestyle data will include:1. Location information2. Driving information and movement information3. His affective state and average cognitive state4. Habitual information—diet, drinking, etc.5. Real-time information about physical health

The span of time and monitoring parameters will be determined jointly byuser and concerned agency.

1. Location Information:

The geographical location of a person can give a general idea of theperson's life style and personality. Information like movement overdifferent non-urban terrain is indicative of an adventurous lifestyle.Also information like the places the person visits will highlight manyof the persons traits e.g., location data showing that one visitsMcDonald's everyday indicates that the individual does not have ahealthy lifestyle, compared to an individual who visits the gym on adaily basis. After large enough samples of data are collected, amovement map of the individual can be created that shows frequencies ofvisits to certain locations within a certain range. Using a patternidentification algorithm, doctors or life insurance agencies can moreeasily analyse location data of an individual and correlate this tohis/her lifestyle.

2. Driving Information and Movement Information:

Velocity and acceleration analysis can be done by the GPS on the phoneto determine whether or not the individual is a rash driver. Informationabout speed limits on a majority of roads is present on the maps thatare on smart phones. It can be understood that an individual is drivingif they are on a road that is traversed upon by vehicles. Usually, GPStracking provides an accuracy of within 50 meters. So, the speed of aperson can be determined by dividing each 50-meter path covered by thetime required by the individual to traverse that distance. It will benoted that a person is walking, not driving, on such a road if the speedis significantly below that of the speed limit (like below 10 km/s) foran extended period of time. Even this information is vital, as itinforms that the individual is walking on a road that is meant forvehicles, which in itself is an unsafe behaviour. This behaviour willnot be confused with cars that are just stuck in traffic, becausetraffic patterns are now being updated constantly to smart phones, anddata about the location and time of the traffic can easily be collected.After confirming that the individual is driving on the road, one cancompare the speed of his/her vehicle with the speed to determine whetheror not the person is speeding. Even if the individual whose data isbeing taken down is not the driver, it is important to know if theindividual is at risk by being in the same vehicle as a person who isspeeding. In addition, if the average velocities recorded in each50-meter block are fluctuating highly, and the time taken to cover one50-meter stretch is significantly different than the time taken to coveranother, one can see that the driving is “stopping and going” toofrequently. An accumulation of data about velocity can easily betranslated into acceleration analysis, where the rashness of the driverwith sudden accelerations can be determined.

3. The Affective and Cognitive State:

The user emotional and cognitive data will be obtained from allcommunications taking place in form texting, video chat and audio chatfrom devices like smart phones, tablets computers or laptops. Since thefunctioning of various features of SWAP like profile+ and virtualclassrooms is heavily of dependent on user emotion and cognitive statethe apps can gather data from these features to observe emotional andcognitive states of the user during the period of observation. Thesedata can be combined with location data (considering the fact that theuser is constantly carrying his smart phone) to affect map of theperson. The affect map will show which emotions and mental statecorrespond to specific locations of the individual.

4. Habitual Information:

Various apps and detection mechanisms can be utilised to determinevarious habits of the user like eating habits, drinking habit, smokinghabit, etc. Apps like Mealsnap, etc. can be detected by the advancedapps of SWAP and used to detect traits of the user.

5. Physical Health Information:

Smart phones have pedometers installed in them and also have thecapacity to find a person's pulse. All these features can be used byadvanced SWAP apps to give a person's physical health status which canbe further combined with time and location information supplement theabove-mentioned data.

From this network, an emotional map can also be constructed that showswhich emotions correspond to specific locations of the individual. Thislocation tracking combined with the audio vector and typing analysis canindicate which locations the individual should continue going to boosthappiness and which locations should be avoided, as they may becorrelated to stress, anger, sorrow, etc.

Emotion Analysis

The large amount of data that will be passing through SWAP will beanalysed in following ways:

1. Video Analysis 2. Speech Analysis

3. Typing analysis

FIG. 10 illustrates an embodiment of how the media acquired by SWAP isgoing to be analyzed. The data can be organized into three segments:Video, Text, and Audio. Pupillary dilation analysis and facial featureanalysis can be taken from the video data analysis. From textual data,keywords, knowledge-based artificial neural networks, typing speed,pressure, contextual clue and error analyses can be done. From audiodata, features can be extracted and analyzed. These can be used todetermine emotion.

Video Analysis

a. Facial Emotion RecognitionThe emotion of user is recognized by tracking the movements of somefixed points of the face like the corners of eyes, mouth boundary, etc.The amount of movement of these points in various frames of the videoare constantly monitored and the data thus generated is fed in variousclassifiers like Bayesian Networks, Decision Trees etc. from which wefind the emotion of the user.b. Pupillary DilationDilation of pupils is common phenomena. The causes for dilation ofpupils are:1. Mental stress (cognitive load).

2. Emotion

3. Light stimulus

Our pupils tend to dilate in different emotional situation. Studiesconducted have shown that with increase in arousal level the diameter ofout pupils increase. Also valance causes our pupils to dilate. But theamount of dilation caused for positive and negative emotion has beenfound out to be the same. This issue may be resolved with further studyin this area—analyzing the rate of dilation and dilation period and alsothe amount and rate of dilation under combination of different stimuli.Also, while measuring pupil dilation, the dilation caused due otherstimuli like light have 2 either ignored or factored out (more study isrequired in this area). Pupillary dilation is a complete involuntaryreflex and hence there no change for us to consciously control it. (Thisis possible in case facial emotion recognition.) Hence no emotion fakingis possible. A distinct difference is apparent for male and femaleusers. So gender classification can be done easily through study ofpupil dilation pattern.

2. Speech Analysis

To find out emotion from speech the basic idea is to study the way thevoice box functions while producing speech under different emotionalstates. Depending upon how it functions variations in wave form appear.By extracting the various features of the waveform from which thesevariations can be detected and putting these (certain combinations offeatures) into various soft computing models the emotion can bepredicted.

Data extracted from an audio vector can be used to determine one'semotional state. The volume and pitch of the speaker can be foundwithout actually recording what the speaker is saying, avoiding anyinvasion of privacy. The content of the conversation is immaterial tothe 3^(rd) parties, since only the tonal nature (loudness and frequency)of the individual is being analyzed.

To find emotion from speech first we extract various components ofspeech, which carry data with respect to emotion. These components areenergy, pitch, cross sectional area of vocal tract tube, formant, speechrate and spectrum features and spectral features like linear predictioncoefficients (LPC), linear prediction cepstrum coefficients (LPCC), Melfrequency cepstrum coefficients (MFCCs) and its first derivative andlog-frequency power coefficients (LFPCs). All these components areextracted from the original speech waveform using various mathematicaland statistical techniques. The features can be extracted utilizingvarious combinations of the features. These acoustic features are usedto find out emotions through various classifiers.

Methods that classify emotions from prosody contours are neuralnetworks, multi-channel hidden Markov model, mixture of hidden Markovmodels these give prediction from the temporal information of speech

Methods which classify emotions from statics of prosody contours supportvector machines, k-nearest neighbours, Bayes classifiers using pdf(probability distribution functions) generated by Parzen windows, Bayesclassifier using one Gaussian pdf, Bayes classifier using mixture ofGaussian pdfs.

Hence from the above-mentioned soft computing techniques we find theemotion of a person. From this his type of collection over a large spanof time, general emotional status can be determined via the audiovector.

Data extracted from an audio vector can be used to determine one'semotional state. The volume and pitch of the speaker can be foundwithout actually recording what the speaker is saying, avoiding anyinvasion of privacy. The content of the conversation is immaterial tothe 3^(d) parties, since only the tonal nature (loudness and frequency)of the individual is being analysed.

Typing Analysis

We will utilize the following methods to kind emotion of the user fromthe text that he types. All the methods will be working in parallel.1. Finding emotional keywords in textual data and deriving the emotionof the sentence from that.2. Finding emotion from sentences, lacking emotion key words usingKnowledge Based Artificial Neural Networks.3. By analyzing the typing speed. The various features of typing that westudy are time lag between consecutive keystrokes4. Error level. (Number of times corrections are made in the sentences).5. Pressure Analysis—the pressure sequence various features extractedlike mean, standard deviation, maximum and minimum energy difference,the positive energy center (PEC) and the negative energy center (NEC).PEC and NEC are calculated from mean and standard deviation afternormalization).6. Contextual cue analysis weather, lighting, temperature, humidity,noise level and shaking of the phone

The various features of typing that we study are time lag betweenconsecutive keystrokes, number of times back space is used, typing speedand pressure put behind each keystroke, for example, from the pressuresequence various features extracted like mean, standard deviation,maximum and minimum energy difference, the positive energy centre (PEC)and the negative energy centre (NEC). PEC and NEC are calculated frommean and standard deviation after normalisation). Apart from thesevarious contextual cues are also taken into account like weather,lighting, temperature, humidity, noise level and shaking of the phone,and the frequency of certain characters, words, or expressions can beused to determine emotion. The above-mentioned sets of features are fedinto various soft computing models (like support vector machines,Artificial neural networks, Bayesian networks, etc), these generateprobability towards a particular emotional state individually for eachset of features. Also, since in most cases the outcome will be towardsthe same emotion from computations on each feature set hence fusionmethods can be used to compute the over all probability of having thatparticular emotion by combining the individual results.

Towards Development of a Model for Emotion Detection from TypingAnalysis

First, we find out features of typing which is exhibited by most peopleand features of these patterns which detect emotions. We now developvarious soft computing models which allow for the detection of aparticular emotion from the typing pattern. To see the efficiency andfunctionality of these models we conduct sample studies where a softwareis downloaded by the people whose typing pattern will be analysed. Apartfrom the typing pattern detection another detection method will also bethere to measure the emotional state at the time of typing. These 2methods will work in parallel and the emotion detected by latter methodwill be taken as reference and later during analysis it will be seenwhether the emotion predicted by the former method matches with thereference.

In the latter method the peoples' emotional valence will be detected bystudy of their facial muscles which can be done by use of a simpleweb-cam (generally available with their computer or laptop) and arousalwill be detected by measuring the galvanic conductivity of skin measuredwith wristband with this capability (already a commercial productmanufactured by a company called Affectiva).

The above-mentioned method departs away from way experiments have beendone on typing analysis recently. In these experiments the candidateswhose pattern will be analysed are given the software which analyses thetyping pattern but reference emotion is found out through questionnairesthat enquire about the emotion of the person before he starts to type.

Again, this will not be a privacy issue because these third parties willnot access full texts. They will just automatically search through themfor the frequency of specific words or expressions that may correlate tothe individual's emotions. These data will not just be collected once,but over a long span of time. As a result, the overall emotional andbehavioural state of individual will be determined. So, a person typingvery fast on a shaking phone, with high pressure under the keys, andusing a high frequency of unpleasant words used in his/her texts canreveal anger or stress. However, if data that points to this behaviouris only collected once or twice in a span of a month, it will not beregarded as very important, as everyone has some infrequent expressionsof anger or stress. However, if a majority of typing data is like this,a doctor of insure company can infer that the individual is constantlyangry or stressed out, which is not good for health.

Mental Health Tracker

Currently 1 in 4 Americans have a mental disorder. It is becomingincreasingly important to identify mental disorders at younger age, whensymptoms are still slight. It is thus essential for primary carephysicians in addition to psychiatrists to be able to recognize mentaldisorders.

In an embodiment, the DSM IV-TR (Diagnostic and Statistical Manual forMental Disorders) and DSM IV-PC (Diagnostic and Statistical Manual forPrimary Care) version, which are the manuals used by doctors todetermine both the presence and category of mental disorder, could beincluded in as part of a computerized algorithm to help doctors forpatient tracking. The DSM IV-PC (meant for primary care physicians, whoare not specialized in mental disorders) has organized symptoms thatcreate a diagnostic algorithm. This manual is concise and fullycompatible with the wider used DSM IV-TR, which is used by psychiatrics.

Primary care physicians (PCP) have made many initial diagnoses of mentaldisorders. However, many diagnoses remain undetected, as PCPs generallyonly have check-ups with patients one or twice a year, and mentaldisorders, at first may be difficult to observe, as there are nostandardized tests for mental disorders. Due to the difficulty indiagnosing a mental disorder within the limited face-to-facepatient-doctor interaction, it can be extremely helpful for doctors touse a non-invasive patient tracking method of an embodiment as shown inFIG. 11, which shows the main aspects of SWAP that can be used to createa profile of the patient that can then be analyzed by the algorithm ofthe DSM-IV and by doctors.

Doctors can track their patients using methods detailed in otherexamples of our patent. FIG. 12 shows a flow diagram that delineatespossible tracking mechanisms. FIG. 12 shows that the proposed trackercan use video data, time and location analysis, typing analysis, andaudio data in order to understand the patient's emotional state. Over aweek or month long analysis, this tracker will then use an algorithmfrom the DSM-IV in order to identify an initial mental diagnosis. Withthe use of the guidelines in the DSM-IV-PC, the algorithms created bythe manual can be used along with our tracking system to provide aprimary initial screening for patients for detection and type of mentaldisorder. Thus, SWAP's Mental Health Tracker can help a physician betterunderstand his patient's needs.

An embodiment relates to a method of establishing a collaborativeplatform comprising performing a collaborative interactive session for aplurality of members, and analysing affect and cognitive features ofsome or all of the plurality of members.

An embodiment could include some or all of the plurality of members fromdifferent human interaction platforms interact via the collaborativeplatform.

An embodiment could include displaying of targeted advertisements ornotifications based on the context of the interactive collaborativesession.

An embodiment could include measuring effectiveness of the displaying oftargeted advertisements or notifications.

An embodiment could include integrating an application or a devicewithin the collaborative interactive session.

An embodiment relates to a computer implemented system comprising: astorage medium configured to store a collaborative interactive sessiondata; and a processor configured to perform a collaborative interactivesession for a plurality of members, wherein the system analyses affectand cognitive features of some or all of the plurality of members.

An embodiment could include some or all of the plurality of members fromdifferent human interaction platforms interact via the collaborativeinteractive session, wherein the different human interactions platformscomprise social media platforms.

An embodiment could include the system being further configured todisplay targeted advertisements or notifications based on the context ofthe interactive collaborative sessions.

An embodiment could include the system being further configured tomeasure effectiveness of the displaying of targeted advertisements ornotifications.

An embodiment could include the system being further configured tointegrate an application or a device within the collaborativeinteractive session.

An embodiment could include a sound and/or video hub, wherein the soundand/or video hub allows any member of the plurality of the members toplay a song and/or a video and simultaneously allows some or all of theplurality of members to listen and/or watch the song and/or the videoplayed.

An embodiment could include audio and/or video synopsis of thecollaborative interactive session for the plurality of members using asound and image-processing technology that creates a summary of anoriginal full-length audio and/or video.

An embodiment could include the system being configured to determine amental health of a patient by analyzing one or more of audio, video,textual and location data of the patient, and evaluating the data in astandardized model.

An embodiment relates to a tangible non-transitory computer readablemedium comprising computer executable instructions executable by one ormore processors for establishing a collaborative platform comprisingperforming a collaborative interactive session for a plurality ofmembers, and analyzing affect and cognitive features of some or all ofthe plurality of members.

An embodiment could include some or all of the plurality of membersinteract from different human interaction platforms.

An embodiment could include computer executable instructions executableby one or more processors for displaying of targeted advertisements ornotifications based on the context of the interactive collaborativesessions.

An embodiment could include the executable instructions comprisinginstruction for determining a mental health of a patient by analyzingone or more of audio, video, textual and location data of the patient,and evaluating the data in a standardized model.

SWAP and Remotely Providing Healthcare

The SWAP platform is useful in multiple aspects of healthcare for bothpatients and physicians. The ability for the SWAP interface to be easilyaccessed by doctors and patients throughout the world tremendouslyimproves healthcare delivery. In addition, SWAP has the ability to beseamlessly integrated with many of the existing and upcoming virtualhealthcare technologies.

FIG. 13 describes an overview of SWAP's innovation in healthcaredelivery. Overall, SWAP provides a dynamic virtual communicationplatform that, in the context of healthcare, allows for heretoforeunparalleled virtual synergies in the complex web of interactionsbetween doctors and patients around the world.

The embodiments of caregiving to a patient include: continuouslymonitoring and measuring the patient using one or more devices; andallowing a caregiver to have real-time interactions with the patientremotely.

One can include real time alerts for the caregiver and optionally thepatient too by not only looking at a single day's data, but optionallyby looking at long term data and optionally comparing long term and/orshort-term data against models of health vitals. Furthermore, holisticanalysis of data can be done by combining short term health data withlong term health data along with the patient profile. Long term healthdata can include health data obtained over a period over a month. Shortterm health data can include health data obtained over a period of aday, an hour, or ten or less minutes. If needed, the caregiver caninteract with the patient remotely as and when a situation arisesrequiring remote interaction. Such a situation may include when a modelof health vitals indicates development of an illness, when a deviationof short-term health data from long term health data, and when real-timemonitored vitals indicate a life-threatening emergency.

The caregiver can provide treatment remotely. Providing treatmentremotely may include sending control signals to adjust doses of medicinegiven to a patient receiving intravenous medications, providinginstructions to the patient, providing instructions to caregivers localto a patient, calling paramedics, etc. The effectiveness of thetreatment can be monitored remotely. Monitoring the effectiveness of atreatment may include receiving health data (long term and/or shortterm) of a patient, receiving report from caregivers local to a patient,receiving signals to an monitor instrument, etc. The treatment can beadjusted remotely based on effectiveness monitored remotely.

Health Care Data Analytics

This tool can be used to diagnose the patient's symptoms usingup-to-date knowledge bases. The data may be already in the SWAPrepository or may be a standalone knowledge base accessible to SWAP.SWAP may be seamlessly integrated into the online knowledge basis(including publicly available and customized software meant for certainillness, etc). It enables doctors to diagnose the illness of patient isa much quicker way. This is called a federated search.

Diagnosis may include: data collection and storage in the knowledgedatabase; patient symptom keywords generation; and query the knowledgedatabase using the keywords. The keywords may be generated using thedata collected from the SWAP platform. The federated search will compilea diagnosis.

Support Groups

SWAP can serve as a social support network for patients. SWAP is also asocial media outlet for patients. If a patient chooses to, he or she mayjoin a support group that has a similar disability or illness. Thesegroups will have doctors overseeing conversations and to answerquestions. Thus, people can connect with other people who have similarillnesses.

Support group members can exchange their data with the support group. Asenior patient could help the newer patients. Patients can make theirown profile. SWAP can be used to help connect patient to healthcarepractitioner or patients of a similar nature. Doctors can be alerted ofdangerous depression related problems: Multiple doctors can work on asingle patient's diagnosis simultaneously; continuous education for thepatient. Communication within the support group can be used to updatethe patients' profiles and become part of the health data of thepatients the healthcare practitioner can access and use.

SWAP could use multiple and dynamic methods of communication to interactwith and monitor patients. SWAP removes fragmentation within videocommunication, a vital tool that is applied to patient-doctorinteraction as well as patient-patient interactions among relateddisease groups. Healthcare professionals have the ability to monitorpatients' symptoms. Through integration with existing health monitoringtechnologies, SWAP serves as an interface for the physician tounderstand the patients' state of being. For example, a plastic surgeonis able to have a consultation via the platform. The surgeon is able totake images of the patient while video chatting, perform pictorialanalyses with the drawing tools, and storing high quality measurementsinto a database.

SWAP enhances home-based monitoring of various chronic conditions.Healthcare professionals can continually monitor their patients'symptoms and overall health, a feature that is useful for diseases suchas obesity and diabetes. There are 4 main categories of monitoring—1)Wellness (height, weight, exercise, etc.), 2) Chronic IllnessMeasurements (BP, glucose, etc.), 3) acute care/rehabilitation 4) aging.Overall, SWAP creates a continuous interaction between chronically illpatients and their physicians.

SWAP's emotion analysis technology can be used to understand patients'mental state while video conferencing. Technologies in the realm ofvideo analysis, speech analysis and typing analysis may be employed.Facial emotion recognition, pupillary dilation, voice box functions,emotional keywords, typing speed analysis, error level, knowledge basedartificial neural networks and pressure analysis, amongst others, may beutilized to collect mental and bodily health data to monitor thepatient. Various patients' behaviour may be used to extract one or moremetrics that characterize the patients' mental state.

Patients unable to express symptoms through traditional video chatting,perhaps due to a language barrier or physical inability, are able toconvey symptomatic information through various other interfaces. Theblackboard interface allows patients to express their current state inmultiple ways. Integration of a translation software has the ability tosurpass the language barrier preventing many doctor-patient interactionsto flourish.

FIG. 14 describes SWAP's ability to provide a dynamic collaborativeplatform with features such as chalkboard interface and mood recognitionto enhance the traditional video conferencing interface.

SWAP can be integrated with multiple other devices. SWAP uses multipleplatforms, thus many of the applications that are already created onsmartphones can be integrated into one combined report. Thus patientscan use multiple home monitoring applications that will present its dataonto the SWAP interface. The SWAP platform may be integrated withphysical measuring devices (e.g., blood pressure cuff or glucose meter).The readings may automatically be inputted in the patient's history. Forexample, a diabetic patient who checks blood glucose level every dayusing a glucose meter can have his readings automatically inputted intothe SWAP patient history section. This can be accomplished through“plug-in” technology similar to a smartphone that can be connected to acomputer.

SWAP is not limited in the way it receives data. For example, Internetis an exemplary way for SWAP to receive data. Other ways may includemobile network, satellite, radio, etc. For example, SWAP can beconnected to cell phones or other mobile devices. People in rural areascan text their conditions to their SWAP account. A doctor may see thesemessages and their response may be texted back to their patients. Thiscan really help people who are in low-income areas and are unable tohave internet access. Also, people who are traveling can be benefitedfrom such an interactive text service. All texts may be saved onto theSWAP platform to facilitate a consolidated patient history.

An integrated search engine may be included in SWAP and allow forincreased doctor's understanding of new scientific discoveries. SWAPintegrated with a search engine that encompass up to date medicalliterature and frontiers in science and medical technology to enhancephysicians knowledge of the most accurate diagnoses, current standard oftherapy and state of the art therapeutics and treatments whileinteracting with the patient. It is currently extremely difficult fordoctors to accurately recall and remain up to date with new datapublished about diagnoses and treatment options. The search engine willenable doctor's type the symptoms of the patient and will quickly givean accurate summary and subsequent detailed analyses of all the medicalliterature currently available that are relevant to the patients'medical conditions. Additionally, the chalkboard interface's academicintegration allows a medical professional to use the power of scientificand diagnostic information available on the web to inform theirdecision.

FIG. 15 exemplifies the added benefits of virtual healthcare deliverythrough SWAP. Integration with state-of-the-art medical databases whileutilizing the SWAP platform to communicate with patients tremendouslyenhances access of information for physicians and allows forunparalleled virtual diagnostic capabilities.

SWAP can serve as a social support network for patients. SWAP is also asocial media outlet for patients. If a patient chooses to, he/or she mayjoin a group that has a similar disability or illness. Such groups canalso work as discussion forums or message boards where people can holdconversations in form of posted messages. The messages may be at leasttemporarily archived. The archived messages can serve as a centralrepository for information about a particular disease and/or condition.Doctors and patients can exchange information about symptoms, diagnoses,treatments, as well as prophylactic measures for particular diseasesand/or conditions. Each “thread” is, in general, specific to a conditionor disease. Once a patient and/or doctor posts a message to a thread,other patients and/or doctors can see the message and respondaccordingly. Such message may be posted anonymously to protect theprivacy of the patients.

Alternatively, such groups can work as chat rooms where people can holdconversations in real-time and get suggestions and solutions torelatively more urgent matters. Like the discussion forums, the chatrooms can allow patients and/or doctors to discuss symptoms, diagnoses,treatments and/or prophylactic measures anonymously.

There can be separate and dedicated web-based and/or mobile applicationinterfaces for various aspects of SWAP. For example, there can be aseparate application for the discussion forum, another separateapplication for the chat room, yet another application for monitoringphysical and/or emotional data. Alternatively, all the various aspectsof SWAP can be integrated into one single interface through whichseparate applications can be called on as needed. In either case,personal data on SWAP can be protected by a single-step authenticationprocess such as a login and a password or a pattern, or a 2-stepauthentication process requiring a frequently refreshed pseudo-randomnumeric, alphabetical, alphanumeric or other phrase required to accessthe information. Alternatively, biometric authentication such as, forexample, iris scan, face-recognition, fingerprint recognition, voicerecognition, or any other biologically unique characteristic may be usedas a means to protect the data accumulated through SWAP. These groupswill have doctors overseeing conversations and to answer questions.Thus, people can connect with other people who have similar illnesses.

This application will be SWAP may organized interactions into severalspheres known as “globes”. Each globe will provide a base interactionfor multiple users to collaborate. SWAP's interface may be customizableto the user's preference. Based on his or her interests, involvements oractivities, the user may be able to select the globes, and the platformsof interaction therein that pertain to themselves and add the selectedglobes to his or her own personalized interface. SWAP may allow users tocreate and publish their own globes for private or public use. Forexample, the social networking platform can use SWAP's sound hubfeature. Doctors or other social networks friends can play therapeuticmusic that all those included can hear. Listening to music togethermakes it a social experience and thus increases its therapeutic value.Also, the music can be reached across the world simultaneously.

SWAP may include an arcade feature that allows patients withpsychological disorders to play medical games, or for geriatric patientsto benefit from cognitive and memory building exercises. Through SWAP,patients can interactively participate with each other.

The way most social networking sites function, they mainly act as agreat platform for data storage, sharing and communication. But theythese are all a far cry from true social interaction simulation. Inother words, in no way are these anywhere near how we interact insociety. Thus the profiles of SWAP will be a system which will be muchcloser to how we remember people, conversations and moreover how weforget. The large amount of data that get passed through the SWAPplatform will be analyzed and this data will be used to shape the SWAPprofiles. The way other people's SWAP profiles will appear to us will besimilar to how we remember people in reality. In this area we try tomimic the way in which we remember people. The profile's emotion feelwill be the general emotion that we generally exhibit when wecommunicate that with that person through any form of media (video, textor speech) (obtained from analyzed data from conversations takingplace). Keeping in trend with how we remember people in reality, sincehow a person is seen by is strongly shaped with event and experiences weshare with that person. The profile of the person will bear events,having strong emotions behind them. Any sort media—like text, speech,video or pictures. Texts can be presented simply as they are, videoswill we presented like snapshots with the option to be played by theuser. The profile of SWAP will be dynamic in nature constantly changingreflecting the mental state of the user. The real-time mental state willbe determined from the various analysis methods, which will be appliedon the data passing through SWAP. Under a state of extreme emotion suchas depression the user profile will be able to reflect this state. Thiswill allow for other people to be notified of the user's emotional stateand hence help him get back normalcy through communication. Throughanalysis ‘close friends’ can also be identified who under theabove-mentioned situation will be notified.

The analysis of data through SWAP will allow the application to identifypeople with whom the user has discussions of high emotional content. Adatabase of sorts can be created which will store people with whom theuser has discussion of high emotional content such as high positiveemotion content, high negative emotion content, people with whom throughcommunication emotion changes from negative to positive. Also, peoplewith whom there isn't communication of high emotion content but volumeand frequency of communication is very high, these people will also beidentified as ‘close friends’. Whenever the user is in a state ofemotional extreme then the user's profile will be highlighted in thehomepages of the ‘close friends’.

Multiple health professionals can see a patient simultaneously. The SWAPinteraction model facilitates online interactive communication formultiple players necessary for remote healthcare delivery. For example,primary care physicians, nurses, speciality physicians and the patientcould all dynamically interact to arrive at the correct diagnosis.

SWAP allows multiple physicians around the world to collaborate and cometo a diagnosis on a patient, as it serves as a great interface to shareinformation such as patient history, scientific insight and medicalexpertise. A doctor can transfer patient information to doctors who canbest understand the patient's needs. This is both in terms of medicalspeciality and culture (including language).

For students who have conditions, doctors can directly present theschool nurses with the relevant medical information of students. Also,for students with learning disabilities etc. teachers can sendinformation to the doctors regarding the student's learning progress.SWAP is also an excellent platform for insured patients who aretravelling. They can still regularly see their personal physician viathe internet.

SWAP allows for medical professionals to disseminate information tomultiple parties simultaneously in the interactive platform. Forexample, a surgeon in Washington, D.C. is able to display a video of aspecific procedure to multiple colleagues around the world while videoconferencing and using the chalkboard interface to take notes. SWAP canbe used for medical education, as it serves as the perfect interface formedical students to watch live videos amongst other students and takegroup notes, etc. The platform will protect all HIPAA laws whentransferring such information to students. SWAP can be used by residentsand doctors as an evaluation technique.

FIG. 16 describes the ability of SWAP healthcare delivery to formcollaborations in treating a patient. Here, an obese patient that islikely to have complications in various therapeutic areas is able to besimultaneously explored by multiple physicians from around the world,along with his close family and support system provided by SWAP socialnetworks.

SWAP can consolidate patient information and history. Conversationsbetween doctors and patients can be summarized using the chatting threadwith affect quantum. The basic flaw which makes social interactionsunrealistic is that every bit of data is remembered which not case inreal day-to-day life interactions is. To replicate these communicationsthat will be happening through SWAP will follow a similar pattern. Thecomments of the thread will slow start to deteriorate i.e. fade away.The period after which the part of the thread is completely forgottenwill be a sort of threshold time, which will be close to average humanbeing time for memory retaining. Memories having high cognitive strainor emotion attached will have much higher threshold time. In otherwords, each quantum of media will have Affect quantum attached to it.

Additionally, patient information gained from symptoms that describedthrough widgets, verbal and written communication are consolidated inthe patient history using the affect quantum method described above.

Also, all information gained from external devices (e.g., glucometer) isstored and captured into a graph so that patient information is neatlytracked and displayed in a easy to read manner. All textingconversations are also recorded and major conversations are highlightedusing the affect quantum method. Lastly, the patient's personalizedprofile serves as an overview for of the patient's basic information,close friends, and mood.

FIG. 17 describes SWAP's ability to collect critical data from patientinteraction and consolidate into a patient's profile for subsequentanalyses.

SWAP can provide educational health care resources to patients. SWAPallows physicians to explain conditions to patients via interactiveinterfaces, such as video, blackboard interface and eLearningtechnology. This is especially helpful for children, in which cases itis often difficult for them to understand their conditions. SWAPharnesses the capabilities of mobile and tablet technology as well asits touch screen technology to allow users to interact with thechalkboard through a much more seamless and natural medium. Furtheringthis concept of seamless, our product will incorporate handwritingrecognition software that will be able to decipher and identify what theuser is writing based on the domain selected and the context of theinformation already present, to convert the users' handwriting intodigital text that will appear much more legible and clear to all theusers. The various features integrated throughout the SWAP platformallows for continuous patient education even when the healthcareprofessional is absent. For example, interactive exercise modules foroverweight children could serve as tools in the prevention of childhoodobesity.

SWAP can be used as a system that allows humans to send touch remotelyto other humans for medical diagnostic purposes. FIG. 18 shows a flowchart for transmission of two way touch sensation between two people,for example, a doctor and a patient. This system allows for tactileinterfacing while utilizing the visual and auditory channels ofcommunication through the SWAP platform to develop a comprehensivemethod of medical examination to further the current state of remotemedicine. The receiver or the patient will wear a jacket embedded withtouch sensitive chips that can stimulate a particular area of skin tocreate the sensation of touch. The sender or doctor will use a medicaldoll to pinpoint specific areas of contact. By touching a certain areaon the doll, a computer will convert that information and send itthrough the Internet, which the jacket will then receive, translating itinto an electrical impulse that models the physical sensation of touch.

The current capabilities of remote medicine are limited to simplecommunication between physicians and patients but have not been expandedto truly simulate the physical aspects of a medical examination. Theimplementation of virtual touch presents a solution to this void in theindustry, allowing doctors to completely characterize a patient'sphysical state.

In one embodiment, SWAP can be used to create a one-way channel of touchcommunication as shown in FIG. 19. For example, if a doctor hopes toassess where a patient's pain lies, the doctor can touch specific areasof the human doll, listening to the patient's response to determinewhich area when touched induces pain. Based on this information, thedoctor can draw a conclusion and reach a diagnosis regarding thepatient's medical condition or injury.

The technology can also be used to establish a channel of two-way touchcommunication. As opposed to drawing a medical prognosis from apatient's verbal response, doctors often have to assess a patient'smedical state by examining his or her physical attributes. For example,if a doctor wanted to examine a patient's throat to check if his or hertonsils were inflamed or swollen, the doctor could do you by placing hisfingers on the area of the doll that corresponds to the patient'sthroat. The doll would then translate that information through theinternet just as if it was a one-way channel of touch, and would then beoutput through the pressure chips embedded in the jacket. In order toassess the shape or the condition of the patient's tonsils, the responsethat the tonsils will have in response to the pressure applied will berecorded. By measuring the elasticity and the plasticity the tissueexhibits, one can determine if it is swollen beyond its normal state.This information can be relayed through either a computer that simplyreports that the tissue is swollen or presents an image of what thetonsils would look like based on its structural integrity, or it can bemanifested through the doll by altering its throat to emulate the shapeand feel of the patient's throat.

Another method of communicating the gesture of touch is through a motiondetection technology. Instead of pinpointing the area of contact youwant to establish by touching a doll or dummy, the motion detectiontechnology can gather hand motions to determine what kind of touchingmotion to simulate, and will then utilize the jacket to illicit thetargeted sensation of touch.

In one embodiment, the interaction is one-way. In one embodiment of atwo-way interaction shown in FIG. 18, the vest itself is able toidentify conditions of the body to the SWAP platform. This informationcan be translated to a remote physical diagnosis. The firmness andstrength of a material can easily be diagnosed. The jacket can also beused to record basic vital signs. One embodiment relates to creating atactile aspect to the interaction wherein the patient could respondverbally.

SWAP Health Platform for Pets

SWAP communication platform can be used for remote diagnosis, treatment,monitoring, and notification of pets by veterinary health careproviders. SWAP health platform can be used for the following scenarios.

Pet owners can consult veterinary health care personnel to diagnose asick pet by using SWAP's multimedia collaboration platforms. Pet ownerswill be able to show their sick pets to a veterinary doctor over thevideo communication channel.

A sick pet's health vitals can be monitored using monitoring devicesthat transmit continuously data to SWAP system. This data can becompared with short term and long term health data of the pet and anyabnormal conditions can be detected automatically and owners can bealerted.

Owners of sick pets can monitor their condition of pet through SWAPplatform when they are away from home.

In addition, using SWAP's touch sensors, owners can remotely create ahugging sensation which can be extremely helpful when the owners areaway from their pets for an extended period of time.

APPENDIX 1

The U.S. patents and publications listed below are hereby incorporatedherein by reference in their entirety. U.S. Pat. No. 8,102,406; Issuedate: Jan. 24, 2102; Method and system for producing a video synopsis,U.S. Pat. No. 8,073,839; Issue date: Dec. 6, 2011; System and method ofpeer to peer searching, sharing, social networking and communication inone or more networks, U.S. Pat. No. 7,523,163; Issue date: Apr. 21,2009; Distributed network system architecture for collaborativecomputing, U.S. Pat. No. 7,313,595; Issue date: Dec. 25, 2007; Systemand method for record and playback of collaborative web browsingsession, U.S. Pat. No. 7,236,926; Issue date: Jun. 26, 2007; System andmethod for voice transmission over network protocols, U.S. Pat. No.6,567,813; Issue date: May 20, 2003; Quality of service maintenance fordistributed collaborative computing, Publication number: US2011/0258125; Filing date: Apr. 14, 2011; Collaborative social eventplanning and execution, Publication number: US 2011/0225519; Filingdate: Feb. 16, 2011 Social media platform for simulating a liveexperience, Publication number: US 2011/0066664; Filing date: Sep. 15,2010; Sports collaboration and communication platform, Publicationnumber: US 2010/0299334; Filing date: Sep. 8, 2009; Computer implementedsystem and method for providing a community and collaboration platformaround knowledge transfer, expertise, innovation, tangible assets,intangible assets and information assets, Publication number: US2010/0332616; Filing date: Aug. 31, 2009; Web guide, Publication number:US 2010/0262550; Filing date: Apr. 8, 2009; Inter-corporatecollaboration overlay solution for professional social networks,Publication number: US 2009/0094039; Filing date: Oct. 4, 2007;Collaborative production of rich media content, Publication number: US2008/0297588; Filing date: May 31, 2007, Managing scene transitions forvideo communication, Publication number: US 2005/0198141; Filing date:Feb. 4, 2005; Secure communications system for collaborative computing,Publication number: US 2003/0167304; Filing date: Dec. 29, 2000;Distributed meeting management, Publication number: US 2003/0164853;Filing date: Dec. 29, 2000; Distributed document sharing, Publicationnumber: US 2013/0046149; Filing date: Aug. 19, 2011; Interactive virtualcare, Publication number: US 2004/0059603; Filing date: Apr. 15, 2003;System and method for virtual health services, Publication number: US2002/0065682; Filing date: May 18, 1999; Virtual Doctor InteractiveCyber yet System, U.S. Pat. No. 8,321,284; Issue date: Nov. 27, 2012;System, method, and program product for delivering medical services froma remote location Publication number: US 2004/0235446; Filing date: Jun.14, 2004; Medical apparatus remote control and method, Publication No.US2012/0259648; Filing date: Apr. 7, 2011; Systems and methods forremote monitoring, management and optimization of physical therapytreatment.

What is claimed is:
 1. A method comprising communicating via a dynamicvirtual communication platform that allows virtual interactions betweena remote caregiver and a patient, the method further comprising:monitoring and measuring the patient using one or more devices, allowingthe remote caregiver to have real-time interactions with the patientremotely, generating real time alerts for the remote caregiver and thepatient by looking at short-term health data and long-term health data,comparing the long-term health data and the short-term health dataagainst models of health vitals, combining the short-term health dataand the long-term health data with a patient profile, wherein thelong-term health data comprises health data obtained over a period of amonth and the short-term health data comprises health data obtained overa period of a day, hours, or minutes, wherein the remote caregiverinteracts with the patient remotely as and when a situation arises thatrequires remote interaction.
 2. The method of claim 1, wherein thesituation comprises when a model of health vitals indicates developmentof an illness, when a deviation of short-term health data from long-termhealth data, and when real-time monitored vitals indicate alife-threatening emergency.
 3. The method of claim 1, wherein the remotecaregiver provides a treatment remotely.
 4. The method of claim 3,wherein providing treatment remotely comprises sending control signalsto adjust doses of intravenous medications given to the patient,providing instructions to the patient, providing instructions to a localcaregiver that is local to the patient, and calling a paramedic.
 5. Themethod of claim 4, further comprising determining effectiveness of thetreatment remotely and adjusting the treatment remotely based on theeffectiveness monitored remotely, wherein the effectiveness is monitoredremotely by receiving the long-term health data and the short-termhealth data of the patient, receiving a report from the local caregiver,and receiving signals from a monitor instrument.
 6. The method of claim1, further comprising performing health care data analytics using datain a knowledge database, wherein the knowledge database comprises arepository of the dynamic virtual communication platform or a standaloneonline knowledge database accessible to dynamic virtual communicationplatform.
 7. The method of claim 6, wherein the dynamic virtualcommunication platform is seamlessly integrated into the standaloneonline knowledge database.
 8. The method of claim 7, wherein thestandalone online knowledge database comprises publicly availabledatabase and customized database meant for a certain illness.
 9. Themethod of claim 8, further comprising diagnosing a symptom of thepatient.
 10. The method of claim 9, wherein the diagnosing comprises:collecting data, storage data in the knowledge database; generatingpatient symptom keywords; and querying of the knowledge database usingthe patient symptom keywords.
 11. A system comprising a dynamic virtualcommunication platform that allows virtual interactions between a remotecaregiver and a patient, the system is configured to: monitor andmeasure the patient, allow the remote caregiver to have real-timeinteractions with the patient remotely, generate real time alerts forthe remote caregiver and the patient by looking at short-term healthdata and long-term health data, compare the long-term health data andthe short-term health data against models of health vitals, combine theshort-term health data and the long-term health data with a patientprofile, wherein the long-term health data comprises health dataobtained over a period of a month and the short-term health datacomprises health data obtained over a period of a day, hours, orminutes, wherein the remote caregiver interacts with the patientremotely as and when a situation arises that requires remoteinteraction.
 12. The system of claim 11, wherein the situation compriseswhen a model of health vitals indicates development of an illness, whena deviation of short-term health data from long-term health data, andwhen real-time monitored vitals indicate a life-threatening emergency.13. The system of claim 11, wherein the remote caregiver provides atreatment remotely.
 14. The system of claim 13, wherein the treatmentremotely comprises sending control signals to adjust doses ofintravenous medications given to the patient, providing instructions tothe patient, providing instructions to a local caregiver that is localto the patient, and calling a paramedic.
 15. The system of claim 14,wherein the system is further configured to determine effectiveness ofthe treatment remotely and adjust the treatment remotely based on theeffectiveness.
 16. The system of claim 11, wherein the system is furtherconfigured to perform health care data analytics using data in aknowledge database, wherein the knowledge database comprises arepository of the dynamic virtual communication platform or a standaloneonline knowledge database accessible to dynamic virtual communicationplatform.
 17. The system of claim 16, wherein the dynamic virtualcommunication platform is seamlessly integrated into the standaloneonline knowledge database.
 18. The system of claim 17, wherein thestandalone online knowledge database comprises publicly availabledatabase and customized database meant for a certain illness.
 19. Thesystem of claim 18, wherein the system is further configured to diagnosea symptom of the patient.
 20. The system of claim 19, wherein the systemis further configured to: collect data, store data in the knowledgedatabase; generate patient symptom keywords; and query the knowledgedatabase using the patient symptom keywords.